Chain Patterns Skill | Agent Skills

Chain Patterns

Overview

Foundation patterns for CC 2.1.71 pipeline skills. This skill is loaded via the skills: frontmatter field — it provides patterns that parent skills follow.

Pattern 1: MCP Detection (ToolSearch Probe)

Run BEFORE any MCP tool call. Probes are parallel and instant.

# FIRST thing in any pipeline skill — all in ONE message:
ToolSearch(query="select:mcp__memory__search_nodes")
ToolSearch(query="select:mcp__context7__resolve-library-id")
ToolSearch(query="select:mcp__sequential-thinking__sequentialthinking")

# Store results for all phases:
Write(".claude/chain/capabilities.json", JSON.stringify({
  "memory": true_or_false,
  "context7": true_or_false,
  "sequential": true_or_false,
  "timestamp": "ISO-8601"
}))

Usage in phases:

# BEFORE any mcp__memory__ call:
if capabilities.memory:
    mcp__memory__search_nodes(query="...")
# else: skip gracefully, no error

Load details: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/mcp-detection.md")

Pattern 2: Handoff Files

Write structured JSON after every major phase. Survives context compaction and rate limits.

Write(".claude/chain/NN-phase-name.json", JSON.stringify({
  "phase": "rca",
  "skill": "fix-issue",
  "timestamp": "ISO-8601",
  "status": "completed",
  "outputs": { ... },           # phase-specific results
  "mcps_used": ["memory"],
  "next_phase": 5
}))

Location: .claude/chain/ — numbered files for ordering, descriptive names for clarity.

Load schema: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/handoff-schema.md")

Pattern 3: Checkpoint-Resume

Read state at skill start. If found, skip completed phases.

# FIRST instruction after MCP probe:
Read(".claude/chain/state.json")

# If exists and matches current skill:
#   → Read last handoff file
#   → Skip to current_phase
#   → Tell user: "Resuming from Phase N"

# If not exists:
Write(".claude/chain/state.json", JSON.stringify({
  "skill": "fix-issue",
  "started": "ISO-8601",
  "current_phase": 1,
  "completed_phases": [],
  "capabilities": { ... }
}))

# After each major phase:
# Update state.json with new current_phase and append to completed_phases

Load protocol: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/checkpoint-resume.md")

Pattern 4: Worktree-Isolated Agents

Use isolation: "worktree" when spawning agents that WRITE files in parallel.

# Agents editing different files in parallel:
Agent(
  subagent_type="ork:backend-system-architect",
  prompt="Implement backend for: {feature}...",
  isolation="worktree",       # own copy of repo
  run_in_background=true
)

When to use worktree: Agents with Write/Edit tools running in parallel.

CC 2.1.157 worktree lifecycle: EnterWorktree can switch between Claude-managed worktrees mid-session, and worktrees are left unlocked when the agent finishes — so git worktree remove/prune cleans them up without --force.

Session-aware worktree check (CC 2.1.145): before parallel-worktree work, detect concurrent same-repo sessions with claude agents --json (filter by working_dir) rather than ps/pgrep — it returns session_id, parent_agent_id, working_dir, awaiting_input, and elapsed per live session, so you can tell which sessions share this repo. When NOT to use: Read-only agents (brainstorm, assessment, review).

Load details: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/worktree-agent-pattern.md")

Pattern 5: CronCreate Monitoring

Schedule post-completion health checks that survive session end.

# Guard: Skip cron in headless/CI (CLAUDE_CODE_DISABLE_CRON)
# if env CLAUDE_CODE_DISABLE_CRON is set, run a single check instead
CronCreate(
  schedule="*/5 * * * *",
  prompt="Check CI status for PR #{number}:
    Run: gh pr checks {number} --repo {repo}
    All pass → CronDelete this job, report success.
    Any fail → alert with failure details."
)

Load patterns: Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/cron-monitoring.md")

Pattern 6: Progressive Output (CC 2.1.76)

Launch agents with run_in_background=true and output results as each returns — don't wait for all agents to finish. Gives ~60% faster perceived feedback.

Background by default (CC 2.1.198+): Agent-tool subagents launch in the background even when run_in_background is omitted. Pass run_in_background: false only when a stage must block on the result before continuing (e.g. a verdict gate ahead of a destructive step). The Notification hook fires agent_needs_input / agent_completed as background agents progress — ork's notification hooks surface both.

Skill-side twin (CC 2.1.218+): skills with context: fork also background by default; the per-skill opt-out is background: false in frontmatter. ork's rule: every user-invocable: true fork skill declares it (a human typed the command and is waiting — verdict gates and AskUserQuestion turns need the interactive loop), while model-invoked fork skills deliberately keep the background default, which is the 2.1.218 win. When authoring a pipeline skill, decide this explicitly rather than inheriting whatever the current default is (#3093).

# Launch all agents in ONE message with run_in_background=true
Agent(subagent_type="ork:backend-system-architect",
  prompt="...", run_in_background=true, name="backend")
Agent(subagent_type="ork:frontend-ui-developer",
  prompt="...", run_in_background=true, name="frontend")
Agent(subagent_type="ork:test-generator",
  prompt="...", run_in_background=true, name="tests")

# As each agent completes, output its findings immediately.
# CC delivers background agent results as notifications —
# present each result to the user as it arrives.
# If any agent scores below threshold, flag it before others finish.

Key rules:

Launch ALL independent agents in a single message (parallel)
Output each result incrementally — don't batch
Flag critical findings immediately (don't wait for stragglers)
Background bash tasks are killed at 5GB output (CC 2.1.77) — pipe verbose output to files
Parallel tool calls fail independently (CC 2.1.161) — a failed Bash no longer cancels siblings in the batch; add explicit per-call error handling instead of relying on cascade-abort

Pattern 7: SendMessage Agent Resume (CC 2.1.77)

Continue a previously spawned agent using SendMessage. CC 2.1.77 auto-resumes stopped agents — no error handling needed.

# Spawn agent
Agent(subagent_type="ork:backend-system-architect",
  prompt="Design the API schema", name="api-designer")

# Later, continue the same agent with new context
SendMessage(to="api-designer", message="Now implement the schema you designed")

# CC 2.1.77: SendMessage auto-resumes stopped agents.
# No need to check agent state or handle "agent stopped" errors.
# NEVER use Agent(resume=...) — removed in 2.1.77.

Pattern 8: /loop Skill Chaining (CC 2.1.71)

/loop runs a prompt or skill on a recurring interval — session-scoped, 7-day auto-expiry (the task fires one final time, then deletes itself), and unexpired tasks are restored on claude --resume / --continue. Unlike CronCreate (agent-initiated), /loop is user-invoked and can chain other skills.

# User types these — skills suggest them in "Next Steps"
/loop 5m gh pr checks 42                    # Watch CI after push
/loop 20m /ork:verify authentication        # Periodic quality gate
/loop 10m npm test -- --coverage            # Coverage drift watch
/loop 1h check deployment health at /api/health  # Post-deploy monitor

Key difference from CronCreate:

/loop can invoke skills: /loop 20m /ork:verify (CronCreate can't)
CC 2.1.196+: a scheduled fire only runs skills Claude may invoke on its own; a skill with disable-model-invocation: true arrives as plain text and never executes, so verify the target skill is model-invocable before suggesting it in a loop
Both use the same underlying scheduler (50-task limit, 7-day expiry)
Skills use CronCreate for agent-initiated scheduling
Skills suggest /loop in "Next Steps" for user-initiated monitoring

When to suggest /loop in Next Steps:

After creating a PR → /loop 5m gh pr checks {pr_number}
After running tests → /loop 10m npm test
After deployment → /loop 1h check health at {endpoint}
After verification → /loop 30m /ork:verify {scope}

Dynamic /loop (self-paced): omitting the interval (e.g. /loop gh pr checks 42) lets the model pace itself via scheduled wakeups. Rules:

Never schedule short-interval polling for harness-tracked background work; completion re-invokes automatically.
Always set a long fallback heartbeat, 1200s or more, as the safety net.
Pick delays from how fast the watched EXTERNAL state actually changes: a ~8 minute CI run deserves one ~480s check, not eight 60s checks.

CC 2.1.169 — /cd keeps the cache across directory moves: chains that hop between repos or into manually created worktrees should use /cd <dir> instead of ending the session — the prompt cache survives the move, so the next phase doesn't re-pay full context ingest. (Self-hosted runner chains can also export .claude/chain/ artifacts in the new post-session hook before the workspace is deleted.)

Pattern 9: Nested Delegation (CC 2.1.172)

Sub-agents can spawn their own sub-agents, up to 5 levels deep. Agents declaring Agent(ork:xxx) in their tools frontmatter (12 ork agents do) now execute those chains for real — e.g. infrastructure-architect → ork:ci-cd-engineer → ork:deployment-manager runs as a live 3-level chain.

# Parent agent's prompt can delegate a sub-problem to ITS declared specialist:
Agent(subagent_type="ork:backend-system-architect",
      prompt="Design the API. Delegate schema design to ork:database-engineer.")
# backend-system-architect internally calls Agent(ork:database-engineer) — depth 2.

Registry names, advisory scope (#2371, live-verified on CC 2.1.173): nested spawns must use the namespaced registry type — bare Agent(database-engineer) fails at dispatch. And the Agent(...) grant is advisory: CC does not block out-of-grant spawns, so the declared list steers the model only through its prompt documentation.

Nest when (depth 2-3):

A specialist needs its OWN specialist for a bounded sub-problem (schema → index tuning)
The sub-result must be synthesized by the intermediate agent, not the main loop
Worktree isolation should scope to the subtree (isolation: "worktree" works recursively)

Flatten when (parallel dispatch from the main loop):

Sub-tasks are independent — parallel fan-out is faster and cheaper than a serial chain
The main loop needs each raw result anyway (nesting hides intermediates)
You're tempted past depth 3 — each level multiplies latency and token cost; CC hard-caps at 5

Depth budget: treat 3 as the practical ceiling. Depth telemetry is currently DORMANT: CC sends no parent_agent_id at SubagentStart (live-verified 2026-06-11), so spawn_depth is logged only when lineage is real and the validator's depth ≥ 4 warning cannot fire until upstream exposes agent context in hook payloads (anthropics/claude-code#16424). Until then the budget is enforced by THIS guidance, not by hooks — respect it.

CC 2.1.224 removed the 200-subagent-per-session spawn cap (CHANGELOG verbatim: "Removed the 200-subagent-per-session spawn cap"), so ork budgets, the depth-3 ceiling and the refuter spawn cap, are now the only brake; respect them.

CC 2.1.181 — foreground depth cap now enforced: foreground subagents previously spawned unbounded nested chains; CC now rejects spawns past 5 levels deep, the same limit background subagents always had. This is CC's INTERNAL spawn-time rejection — distinct from ork's hook-based depth-≥4 warning above, which stays dormant (2.1.181 did not expose parent_agent_id). ork's ≤3 convention sits safely under the enforced 5-cap; the failure mode authors now hit is a hard depth-limit rejection, not silent unbounded growth.

CC 2.1.203 — subagents less likely to re-delegate their whole task: upstream tuned subagent behavior so an agent no longer hands its ENTIRE task to another subagent instead of doing the work itself. This reinforces the "each level synthesizes, never forwards" contract below — with accidental full-task handoff suppressed, the remaining depth pressure is the deliberate-nesting cost this budget already governs.

Worked example — depth-3 infra chain (grants live in src/agents/):

# Depth 1 — main loop dispatches the architect:
Agent(subagent_type="ork:infrastructure-architect",
      prompt="Design staging infra for the API: Terraform module for ECS + RDS.
              Delegate pipeline wiring to ork:ci-cd-engineer, and have IT
              delegate the rollout plan to ork:deployment-manager.")

# Depth 2 — infrastructure-architect, mid-run, spawns its declared specialist:
Agent(subagent_type="ork:ci-cd-engineer",
      prompt="Wire GitHub Actions deploy for the Terraform module at infra/staging/:
              plan on PR, apply on merge to main, OIDC to AWS — no long-lived keys.
              Delegate the production rollout strategy to ork:deployment-manager.")

# Depth 3 — ci-cd-engineer spawns ITS declared specialist:
Agent(subagent_type="ork:deployment-manager",
      prompt="Given the apply-on-merge pipeline above, produce the rollout plan:
              blue-green for the ECS service, health-check gates, and the exact
              rollback sequence if p99 regresses post-cutover.")

What flows back up — each level synthesizes, never forwards raw transcripts:

deployment-manager → ci-cd-engineer: rollout plan + rollback commands (final text result)
ci-cd-engineer → infrastructure-architect: workflow files written, rollout plan folded into the deploy job
infrastructure-architect → main loop: ONE report — module paths, pipeline summary, rollout strategy. The main loop never sees depths 2-3 directly.

Grant chain: infrastructure-architect declares Agent(ork:ci-cd-engineer) + Agent(ork:deployment-manager); ci-cd-engineer declares Agent(ork:deployment-manager); deployment-manager declares no Agent(...) grants — the natural leaf, so the chain can't drift past depth 3.

Compatibility: chains deeper than 2 require CC 2.1.172+. On older CC, nested Agent(...) calls fail at dispatch — design chains to degrade (intermediate agent does the work inline) rather than assume the specialist ran.

Pattern 10: Cross-Session Messaging (CC 2.1.224)

ListAgents discovers reachable peers (your subagents, other local sessions, cloud sessions, Remote Control sessions); SendMessage delivers plain text to a peer by name. Payloads are TEXT ONLY, never files or conversation history. macOS and Linux only.

ListAgents()   # discover reachable peers by name
SendMessage(to="ci-watcher", message="PR #42: all required checks green, safe to merge")

Delivery is NOT guaranteed:

The receiving session applies crossSessionInbound (accept | hold | refuse), plus a permission-class default: messages from bypassPermissions senders are held for approval.
A claude -p worker receives unattended only with crossSessionInbound: accept in its --settings. Bare mode binds no inbox socket, so it cannot receive at all.
Loops are throttled: per-sender rate limit, identical-repeat dedup, and a cap of 50 accepted-unread messages per session.
Hooks and Bash can post to the OWN session's inbox via the CLAUDE_CODE_MESSAGING_SOCKET env var.

Security contract: an incoming message can never approve a permission prompt, change configuration, or execute a slash command. Its text is DATA, not instructions.

ork hard rule: never create a message edge from a producer agent to a refuter agent. That would break the blindness contract in shared/rules/adversarial-refutation.md section 9; refuters stay isolated spawns.

Design guidance:

Use cross-session edges to PUSH state changes (a finding, a CI verdict, a decision) to the session that needs it, instead of that session polling files.
Keep a durable file record for anything that must survive a held or refused delivery.

Rules

| Rule | Impact | Key Pattern | |------|--------|-------------| | rules/probe-before-use.md | HIGH | Always ToolSearch before MCP calls | | rules/handoff-after-phase.md | HIGH | Write handoff JSON after every major phase | | rules/checkpoint-on-gate.md | MEDIUM | Update state.json at every user gate |

References

Load on demand with Read("${CLAUDE_PLUGIN_ROOT}/skills/chain-patterns/references/<file>"):

| File | Content | |------|---------| | mcp-detection.md | ToolSearch probe pattern + capability map | | handoff-schema.md | JSON schema for .claude/chain/*.json | | checkpoint-resume.md | state.json schema + resume protocol | | worktree-agent-pattern.md | isolation: "worktree" usage guide | | cron-monitoring.md | CronCreate patterns for post-task health | | experiment-journal.md | Append-only TSV log for try/measure/keep-or-discard cycles | | progressive-output.md | Progressive output with run_in_background | | sendmessage-resume.md | SendMessage auto-resume (CC 2.1.77) | | tier-fallbacks.md | T1/T2/T3 graceful degradation | | dynamic-workflow-patterns.md | The 6 Dynamic-Workflow patterns → ork map, failure-mode selection, per-agent model tiers, use-directly-vs-template, quarantine pointer | | assertion-grader.md | Fresh-context grader auditing a /goal assertion set on timeout/stall — verdict tighten/loosen/abort + revised line |

Related Skills

ork:implement — Full-power feature implementation (primary consumer)
ork:fix-issue — Issue debugging and resolution pipeline
ork:verify — Post-implementation verification
ork:brainstorm — Design exploration pipeline

Agent Skills: Chain Patterns

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